With recent advances in computerization in medical organizations such as hospitals, an increasing number of organizations have introduced electronic medical charts which manage patient diagnosis information. Each electronic medical chart unitarily manages, on it, the diagnosis history, medication information, surgical information, diseased part images, X-ray images, and the like of each patient, and allows to easily share and reuse data. Recent increases in storage capacity have allowed electronic medical charts to store large quantities of digital images of diseased parts and the like upon image-sensing them.
In such an environment, a technique for storing, in electronic medical charts, images obtained by image-sensing patients using digital cameras as medical records, is frequently used. In a dermatology department, surgery department, and nursing field, the images of wounds, operative scars, and pressure ulcers (bedsores) of patients are periodically sensed by digital cameras to observe temporal changes in the diseased parts.
Recent advances in communication technology have been implementing remote medical care at home. An increasing number of patients themselves now take pictures of diseased parts using image sensing apparatuses such as general-purpose digital cameras, transmit the pictures to medical organizations, and receive diagnoses from doctors. In such a state in which patients themselves perform image sensing, it is difficult, depending on the region of a patient, to capture the proper diseased part image while seeing an output image from an image sensing apparatus.
As a method of solving the problem of difficulty in image-sensing diseased parts, there is conceivable a method of automatically detecting a specific region at the time of image sensing by learning the region. As a detection method, there is available, for example, “Rapid Object Detection Using a Boosted Cascade of Simple Features”, Viola, P. and Jones, M., IEEE COMPUTER SOCIETY CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION, 2001, VOL 1, pages I-511-I-518. This method acquires a feature amount from a teacher image in advance, obtains the feature amounts of all partial images in an input image, and compares the feature amounts with each other to determine whether each partial image is similar to the teacher image.
An image processing method disclosed in Japanese Patent Laid-Open No. 05-180699 detects a diseased part region by using a special marker when it is difficult to detect the diseased part position by surface temperature image sensing.
The method of detecting by learning a diseased part region has a problem that it is difficult to detect temporal changes including improvements and deteriorations in the symptom of a diseased part. In addition, learning from many teacher data including the follow-up of symptoms in a general purpose manner will increase the variance of features, resulting in a deterioration in detection accuracy.